import textract

text = textract.process('ethanfrome11.pdf', method = 'tesseract')
book1 = (text)
from nltk.tokenize import sent_tokenize, word_tokenize

text = textract.process('ethanfrome22.pdf', method = 'tesseract')
book2 = (text)
from nltk.tokenize import sent_tokenize, word_tokenize

import difflib
import nltk
import re

text = textract.process('ethanfrome11.pdf', method = 'tesseract')
book1 = text.decode()

text = textract.process('ethanfrome22.pdf', method = 'tesseract')
book2 = text.decode()

from nltk.tokenize import sent_tokenize, word_tokenize
from IPython.core.display import HTML

words1 = nltk.word_tokenize(book1)
words2 = nltk.word_tokenize(book2)

htmldiff = difflib.HtmlDiff()
tbl = htmldiff.make_table(words1, words2, context = True)
HTML(tbl)

n	n	1	A
		2	TaN
		3	ES
		4	=
		5	Ser
		6	Fr
		7	JOHN
		8	HENRY
		9	NASH
		10	LIBRARY
		11	@
		12	SAN
		13	FRANCISCO
		14	©
		15	PRESENTED
		16	TO
		17	THE
		18	UNIVERSITY
		19	OF
		20	CALIFORNIA
		21	ROBERT
		22	GORDON
		23	SPROUL
		24	,
		25	PRESIDEN
		26	.
		27	Mr.anD
		28	Mrs.
		29	MILTON
		30	S.RAY
		31	CECILY
		32	,
		33	VIRGINIA
		34	anp
		35	ROSALYN
		36	RAY
		37	AND
		38	THE
		39	RAY
		40	OIL